compliance-check
Check license compatibility, data privacy compliance, and AI ethics. Use when adding dependencies, handling user data, or reviewing regulatory requirements.
Best use case
compliance-check is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Check license compatibility, data privacy compliance, and AI ethics. Use when adding dependencies, handling user data, or reviewing regulatory requirements.
Teams using compliance-check should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/compliance-check/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How compliance-check Compares
| Feature / Agent | compliance-check | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Check license compatibility, data privacy compliance, and AI ethics. Use when adding dependencies, handling user data, or reviewing regulatory requirements.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Compliance Check Perform a compliance check with the following scope: $ARGUMENTS ## Compliance Checks ### License Compatibility 1. List all project dependencies and their licenses 2. Verify compatibility with the project's ISC license 3. Flag any copyleft (GPL, AGPL) or restrictive licenses 4. Check for attribution requirements ### Data Privacy 1. Trace user data flow through the application: - Frontend: What data is collected in forms? - Backend: What data is stored, logged, or forwarded? - Agents: What user data is sent to external AI APIs (Google Gemini)? - LangSmith: What data is sent for tracing/observability? 2. Identify PII handling 3. Check data retention practices ### AI Ethics 1. Review AI agent guardrails (secure_agent input/output sanitization) 2. Check for content filtering mechanisms 3. Verify transparency about AI-generated content 4. Review for potential bias in agent behavior ## Output Produce a compliance report: ```text ## Summary: [PASS / NEEDS ATTENTION / FAIL] ### License Compliance: [PASS/FAIL] [Details] ### Data Privacy: [PASS/FAIL] [Details] ### AI Ethics: [PASS/FAIL] [Details] ### Action Items 1. [Priority-ordered list of required changes] ```
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